AI RESEARCH
Using Large Language Models and Knowledge Graphs to Improve the Interpretability of Machine Learning Models in Manufacturing
arXiv CS.AI
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ArXi:2604.16280v1 Announce Type: new Explaining Machine Learning (ML) results in a transparent and user-friendly manner remains a challenging task of Explainable Artificial Intelligence (XAI). In this paper, we present a method to enhance the interpretability of ML models by using a Knowledge Graph (KG). We domain-specific data along with ML results and their corresponding explanations, establishing a structured connection between domain knowledge and ML insights.